python停用词表 更新热词表

Python停用词表已更新，现在包含了最新的热门词汇。这些词汇在文本分析中可能会影响结果的准确性，因此需要被排除在外。

Python停用词表更新热词表

1. 获取停用词表

我们需要从网上下载一个中文停用词表，这里我们使用jieba库的内置停用词表。

import jieba
获取停用词表
stopwords = set(jieba.analyse.stop_words)

2. 读取文本数据

我们需要读取文本数据，这里我们假设文本数据存储在一个名为text_data.txt的文件中。

with open('text_data.txt', 'r', encoding='utf8') as f:
    text = f.read()

3. 分词并去除停用词

使用jieba库对文本进行分词，并去除停用词。

import jieba.posseg as pseg
分词并去除停用词
words = [word for word, flag in pseg.cut(text) if word not in stopwords]

4. 统计词频

使用collections库中的Counter类统计词频。

from collections import Counter
统计词频
word_freq = Counter(words)

5. 更新热词表

将统计出的词频按照降序排列，取前N个作为热词。

更新热词表
hotwords = word_freq.most_common(N)

6. 输出热词表

将热词表输出到文件。

输出热词表
with open('hotwords.txt', 'w', encoding='utf8') as f:
    for word, freq in hotwords:
        f.write(f'{word}: {freq}
')

至此，我们已经完成了Python停用词表的更新热词表操作。

以下是一个简单的介绍，包含了两列：一列是Python停用词表，另一列是更新热词表。

停用词表 更新热词表 a 新冠病毒 about 疫情 above 云计算 after 5G again 人工智能 all 大数据 almost 区块链 along 芯片 also 无人驾驶 always 虚拟现实 among 生物技术 an 量子计算 and any are as at be because been before being below between both but by can could did do does doing down during each few for from further had has have having he her here hers herself him himself his how however i if in into is it its itself just kg km lb left like ln ltd m mg might ml mm more most mr mrs ms much must my myself n no nor not of off often on once only or other our ours ourselves out over own part per perhaps put rather re s same she should since so some such t than that the their theirs them themselves then there these they thick thin this those through to too under until up very was we well were what when where which while who whom why with within without would yet you your yours yourself yourselves

请注意，停用词表是英文的，而更新热词表是中文的，这个介绍仅作为示例，实际上停用词表和热词表的内容可以根据实际需求进行调整，停用词表通常包含一些常见的、没有实际意义的单词，而热词表则包含当前热门的话题或关键词。